Marine three-dimensional airway analysis method and system based on meteorological and hydrological data
Through the three-dimensional marine route analysis method based on meteorological and hydrological data, the A* algorithm is improved, and the changes in current intensity and marine environmental constraints are considered, the problems of failure to effectively consider current changes and marine environmental constraints in the existing technology are solved, and a more efficient and reliable underwater vehicle path planning is achieved.
Patent Information
- Application Number
- CN202411882140.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-19
- Publication Date
- 2025-04-15
AI Technical Summary
The prior art fails to effectively consider the impact of changes in current intensity on the route in the underwater vehicle path planning, and has not fully introduced constraints on the marine environment.
The marine three-dimensional navigation route analysis method based on meteorological and hydrological data is adopted to construct an obstacle matrix by rasterizing the three-dimensional sea environment, and the marine environmental factor function is constructed from the two aspects of thermoclimb and density jump layer, and the dissipation function and heuristic function of the traditional A* algorithm are improved to form the final evaluation cost to achieve more accurate path planning.
This method can carry out path planning more reliably and efficiently, taking into account factors such as ocean currents, obstacles, temperature and density, and improves the navigation capabilities of underwater vehicles in complex marine environments.
Smart Images
Figure CN119826820A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to geographic information, meteorology and hydrology, and route planning, and in particular to a method and system for analyzing ocean stereoscopic routes based on meteorology and hydrology data. Background Art
[0002] As countries around the world continue to pay attention to and compete for marine resources and rights, marine resources are experiencing a blowout development. While gaining benefits, it also brings endless risks. How to use the marine environment to safely and efficiently conduct underwater resource exploration and underwater navigation has become a research direction. In recent years, scholars and experts have conducted a lot of research on the path planning of underwater vehicles from different perspectives such as collision avoidance, heading constraints, environmental interference and energy consumption.
[0003] Yogang Singh et al. proposed an improved A* algorithm, which takes into account the impact of ocean currents on the route of underwater vehicles and adds the constraint of safe distance from obstacles to achieve obstacle avoidance of underwater vehicles and reduce route energy consumption. However, the disadvantage is that it only considers the case of constant ocean current intensity and does not include the impact of changes in ocean current intensity on the method. YAO Y et al. introduced dynamic obstacles based on D*lite, but did not further introduce constraints of the marine environment. Summary of the invention
[0004] The purpose of the present invention is to provide a method and system for analyzing ocean stereoscopic routes based on meteorological and hydrological data.
[0005] The technical solution to achieve the purpose of the present invention is: a method for analyzing ocean stereoscopic routes based on meteorological and hydrological data, comprising the following steps:
[0006] Step 1: Use the grid method to divide the selected three-dimensional sea environment into m×n×l grid units of the same size, each grid unit represents a relatively independent environmental unit;
[0007] Step 2: Place the inaccessible area elements in the rasterized sea area, construct the obstacle matrix of the map environment model, and represent the free passage units and obstacle units;
[0008] Step 3: Construct functions of the ocean environment factors that affect the underwater vehicle route from the two aspects of thermocline and density cline;
[0009] Step 4: Based on the ocean environment, the dissipation function g(p) and heuristic function h(p) of the traditional A* algorithm are improved, and the ocean environment information such as the temperature jump layer and density jump layer of the grid sea area are combined to form the final evaluation cost f(p);
[0010] Step 5: Perform path planning in the sea area with the minimum evaluation cost to form a proposed route plan for the underwater vehicle.
[0011] Furthermore, in step 1, the selected three-dimensional sea environment is divided into m×n×l grid units of the same size using a grid method, and each grid unit represents a relatively independent environmental unit. The specific method is as follows:
[0012] Select the expected starting and ending points of the underwater vehicle on the map, set the planned diving depth and the deepest diving depth of the underwater vehicle, and use the grid method to grid the three-dimensional sea environment. The gridding scale is based on the diving speed and path accuracy requirements of the underwater vehicle itself, and the sea environment is divided into m×n×l grid units of the same size.
[0013] Further, step 2: place the inaccessible area elements in the rasterized sea area, construct the obstacle matrix of the map environment model, and represent the free passage unit and the obstacle unit, where:
[0014] Elements of impassable areas include submarine obstacles, shipwrecks, reefs, sea basins, sea ridges, trenches, derricks, offshore platforms and oil and gas fields.
[0015] Furthermore, in step 2, the elements of the impassable area are placed in the rasterized sea area, and the obstacle matrix of the map environment model is constructed to represent the free passage units and obstacle units. The specific method is as follows:
[0016] The binary barrier information of any grid cell in the environment is defined as follows:
[0017]
[0018] Among them, (x, y, z) represents the position coordinates of grid p;
[0019] The obstacle matrix of the map environment model is expressed as:
[0020] map[m][n][l]={p(i,j,k),0≤i≤m,0≤j≤n,0≤k≤l}
[0021] Among them, m, n, and l represent the number of grids divided by the x-axis, y-axis, and z-axis respectively, i represents the x-axis coordinate value of point p, j represents the y-axis coordinate value of point p, and k represents the z-axis coordinate value of point p.
[0022] Furthermore, in step three, functions are constructed for the marine environmental factors that affect the underwater vehicle route from the two aspects of thermocline and density cline. The specific method is as follows:
[0023] Step 3.1, establish the thermocline environment function:
[0024]
[0025] Among them, K p represents the thermocline strength of grid cell p, Z k and T k Represents the depth and water temperature of the point p with a z-axis coordinate value of k in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis.
[0026] Step 3.2, establish the density jump layer environment function:
[0027]
[0028] Among them, ρ p represents the density jump strength of grid cell p, Z k and ρ k Indicates the depth and density of the z-axis coordinate value k at point p in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis.
[0029] Furthermore, in step 4, the dissipation function g(p) and heuristic function h(p) of the traditional A* algorithm are improved based on the ocean environment, and the ocean environment information such as the temperature jump layer and density jump layer of the grid sea area are combined to form the final evaluation cost f(p). The specific method is:
[0030] Step 4.1, establish the energy consumption model of underwater vehicle:
[0031] W=W X +W Y +W Z =Σ i＝1 (τ Xi x i +τ Yi y i +τ Zi z i )
[0032] Σ i＝1 (τ Xi +τ Yi +τ Zi )=τ
[0033] Where W represents the total energy of the underwater vehicle, τ represents the number of grids where the underwater vehicle consumes all the energy to dive, and W X ,W Y ,W Z They represent the energy consumed by the underwater vehicle in the X, Y and Z directions respectively, i ,y i ,z i Respectively represent the unit length of the grid that the underwater vehicle passes through in the X, Y and Z directions, τ Xi ,τ yi ,τZi They represent the number of grids in which the underwater vehicle consumes all its energy to dive in the X, Y and Z directions respectively;
[0034] Step 4.2, define the dissipation function g(p):
[0035] The temperature jump layer and density jump layer environment function are introduced, and the energy consumption of the underwater vehicle moving from the current grid to the next adjacent grid is defined as the dissipation function g(p), which is expressed as:
[0036]
[0037] In the formula, K p represents the thermocline environment function, ρ p represents the density jump layer environment function.
[0038] Step 4.3, define the heuristic function h(p):
[0039] The average speed of the grid passed by the connection between the intermediate node and the end point, that is, the end point fitness, is defined as the heuristic function h(p), which is expressed as:
[0040]
[0041] Among them, p is the current node number, ω is the weight coefficient, is the average speed of the grids passed by the line connecting the current node and the end point, v max is the speed of the grid with the maximum speed among the grids that the line passes through, and m is the number of grids that the line passes through;
[0042] Step 4.3, construct the final evaluation cost function
[0043] The final evaluation cost function f(p) is expressed as:
[0044]
[0045] A marine stereoscopic route analysis system based on meteorological and hydrological data implements the marine stereoscopic route analysis method based on meteorological and hydrological data to realize marine stereoscopic route analysis based on meteorological and hydrological data, and is divided into five modules, which respectively execute steps 1 to 5.
[0046] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the ocean stereoscopic route analysis method based on meteorological and hydrological data is implemented to realize the ocean stereoscopic route analysis based on meteorological and hydrological data.
[0047] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the ocean stereoscopic route analysis method based on meteorological and hydrological data is implemented to realize the ocean stereoscopic route analysis based on meteorological and hydrological data.
[0048] Compared with the prior art, the present invention has the following significant advantages: it comprehensively considers various factors in the marine environment, including constraints of the marine environment such as ocean currents, obstacles, temperature, density, etc., to cope with real-time changing environments and complex constraints, thereby achieving more reliable and efficient path planning and improving the navigation capability of vehicles in complex marine environments. BRIEF DESCRIPTION OF THE DRAWINGS
[0049] Figure 1 It is a flow chart of a method for analyzing ocean stereoscopic routes based on meteorological and hydrological data;
[0050] Figure 2 It is a schematic diagram of the discretization of sea obstacle factors;
[0051] Figure 3 It is a schematic diagram of the thermocline;
[0052] Figure 4 is the vertical distribution of the density jump layer calculated by the seawater density and vertical gradient method;
[0053] Figure 5 It is a diagram of node endpoint fitness. DETAILED DESCRIPTION
[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0055] A method for analyzing ocean stereoscopic routes based on meteorological and hydrological data comprises the following steps:
[0056] Step 1: Use the grid method to divide the selected three-dimensional sea environment into m×n×l grids of the same size. Each grid represents a relatively independent environmental unit, dividing the complex and changeable sea environment into units that are easy to manage and analyze.
[0057] Select the desired starting and ending points of the underwater vehicle on the map, input the planned diving depth (m) and the deepest diving depth (m) of the underwater vehicle, and use the grid method to grid the three-dimensional sea environment. The scale of the gridding is based on the diving speed and path accuracy requirements of the underwater vehicle itself, and the sea environment is divided into m×n×l grids of the same size. The larger the unit grid, the rougher the environmental model, and the lower the accuracy of the planned path, but the advantage is that the algorithm's search time is short. The smaller the unit grid, the finer the environmental model, and the advantage is that the path is more accurate, but the number of calculations of the algorithm increases exponentially, and the calculation time increases significantly. Therefore, the scale of the gridding should be adjusted according to actual needs to find a balance between the accuracy of the path and the calculation efficiency of the algorithm.
[0058] Step 2: Place the inaccessible area elements such as submarine obstacles, shipwrecks, reefs, sea basins, sea ridges, trenches, derricks, offshore platforms, oil and gas fields in the rasterized sea area and discretize them into a matrix form.
[0059] like Figure 2 , the actual movement of the underwater vehicle can be simplified into the movement of a rigid body on a plane. The position and size of static obstacles in the stealth environment are known. In order to avoid the underwater vehicle colliding with obstacles during stealth, only cells without any obstacles in the grid are considered to be free-travel cells, otherwise they are all considered obstacle cells. The expansion processing of obstacle grid cells is to expand all grids containing obstacles to the size that completely covers the cells. In order to represent the information of the grid, it is agreed that the free grid is white and the obstacle grid is black.
[0060] The grid position can be obtained by the coordinate method. Considering that the grid obstacle information is binary, the information of each position can be discretized into a matrix form so that it can be stored in the form of an array in the computer. The obstacle binary information of any grid unit in the environment is usually defined as follows:
[0061]
[0062] Among them, (x, y, z) represents the position coordinates of p.
[0063] The matrix form of obstacles in the map environment model can be expressed as:
[0064] map[m][n][l]={p ijk ,0≤i≤m,0≤j≤n,0≤k≤l}
[0065] ={p(i,j,k),0≤i≤p,0≤j≤q,0≤k≤n}
[0066] Among them, m, n, and l represent the number of grids divided by the x-axis, y-axis, and z-axis respectively, i represents the x-axis coordinate value of point p, j represents the y-axis coordinate value of point p, and k represents the z-axis coordinate value of point p.
[0067] Step 3: Construct functions of the marine environmental factors that affect the route of underwater vehicles from the two aspects of thermocline and density cline.
[0068] Define the position coordinates of any grid cell p in the environment as (x, y, z), then the specific steps are:
[0069] Step 3.1, establish the thermocline environment function:
[0070]
[0071] Among them, K p represents the thermocline strength at p, Z k and T k Represents the depth and water temperature of the point p with a z-axis coordinate value of k in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis.
[0072] Step 3.2, establish the density jump layer environment function:
[0073]
[0074] Among them, ρ p represents the density jump layer strength of p, Z k and ρ k Indicates the depth and density of the z-axis coordinate value k at point p in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis.
[0075] Step 4: Improve the dissipation function g(p) and heuristic function h(p) of the traditional A* algorithm based on the marine environment to form the final evaluation cost function f(p).
[0076] Step 4.1, establish the energy consumption model of underwater vehicle:
[0077] W=W X +W Y +W Z =∑ i＝1 (τ Xi x i +τ Yi y i +τ Zi z i )
[0078] ∑ i＝1 (τ Xi +τ Yi +τZi )=τ
[0079] Where W represents the total energy of the underwater vehicle, τ represents the number of grids where the underwater vehicle consumes all the energy to dive, and W X ,W Y ,W Z They represent the energy consumed by the underwater vehicle in the X, Y and Z directions respectively, i ,y i ,z i Respectively represent the unit length of the grid that the underwater vehicle passes through in the X, Y and Z directions, τ Xi ,τ yi ,τ zi They represent the number of grids that the underwater vehicle needs to dive in the X, Y, and Z directions while consuming all its energy.
[0080] Step 4.2, define the dissipation function g(p):
[0081] The temperature jump layer and density jump layer environment function are introduced, and the energy consumption of the underwater vehicle moving from the current grid to the next adjacent grid is defined as the dissipation function g(p), which is expressed as:
[0082]
[0083] In the formula, K p represents the thermocline environment function, ρ p represents the density jump layer environment function.
[0084] Step 4.3, define the heuristic function h(p):
[0085] like Figure 5 As shown in the figure, the starting point is node A, the end point is node B, path 1 and path 2 are two paths of the same length, passing through the intermediate node M and the intermediate node N respectively. The average speed of the grid passed by the connection line between the intermediate node and the end point (i.e., the end point fitness) is defined as the heuristic function h(p), which is expressed as:
[0086]
[0087] Among them, p is the current node number, ω is the weight coefficient, is the average speed of the grids passed by the line connecting the current node and the end point, v max is the speed of the grid with the maximum speed among the grids passed by the line, and m is the number of grids passed by the line. The grid speed with obstacles is 0, and the endpoint fitness of different nodes is determined to determine which node has better optimization ability for the local path.
[0088] Step 4.3, construct the final evaluation cost function
[0089] The final evaluation cost function f(p) is expressed as:
[0090]
[0091] Step 5: Perform underwater vehicle route planning based on the A* algorithm to form a proposed underwater vehicle route. The specific process is as follows:
[0092] (1) Select the desired starting and ending points of the underwater vehicle on the map, and input the planned diving depth (m) and the maximum diving depth (m) of the underwater vehicle.
[0093] (2) Select the type of obstacle area, select the location, and select the hydrological factors to be considered.
[0094] (3) Based on raster data, the A* algorithm is used to realize the path finding planning of underwater vehicles in complex ocean environments. f(p) is defined as the final evaluation cost, g(p) is defined as the cost paid, and h(p) is defined as the expected cost.
[0095] (4) According to the calculation result of the final evaluation cost f(p), the underwater vehicle is submerged in the sea area at the minimum cost to form a route proposal. The algorithm process is shown below.
[0096]
[0097]
[0098] The present invention also proposes a three-dimensional ocean route analysis system based on meteorological and hydrological data, implements the three-dimensional ocean route analysis method based on meteorological and hydrological data, realizes three-dimensional ocean route analysis based on meteorological and hydrological data, and is divided into five modules, executing steps 1 to 5 respectively.
[0099] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the ocean stereoscopic route analysis method based on meteorological and hydrological data is implemented to realize the ocean stereoscopic route analysis based on meteorological and hydrological data.
[0100] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the ocean stereoscopic route analysis method based on meteorological and hydrological data is implemented to realize the ocean stereoscopic route analysis based on meteorological and hydrological data.
[0101] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0102] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for analyzing ocean three-dimensional routes based on meteorological and hydrological data, characterized in that: The steps include: Step 1: Use the grid method to divide the selected three-dimensional sea environment into m×n×l grid units of the same size, each grid unit represents a relatively independent environmental unit; Step 2: Place the inaccessible area elements in the rasterized sea area, construct the obstacle matrix of the map environment model, and represent the free passage units and obstacle units; Step 3: Construct functions of the ocean environment factors that affect the underwater vehicle route from the two aspects of thermocline and density cline; Step 4: Based on the ocean environment, the dissipation function g(p) and heuristic function h(p) of the traditional A* algorithm are improved, and the ocean environment information such as the temperature jump layer and density jump layer of the grid sea area are combined to form the final evaluation cost f(p); Step 5: Perform path planning in the sea area with the minimum evaluation cost to form a proposed route plan for the underwater vehicle.
2. The method for analyzing ocean three-dimensional routes based on meteorological and hydrological data according to claim 1, characterized in that: Step 1: Use the grid method to divide the selected three-dimensional sea environment into m×n×l grid units of the same size. Each grid unit represents a relatively independent environmental unit. The specific method is as follows: Select the expected starting and ending points of the underwater vehicle on the map, set the planned diving depth and the deepest diving depth of the underwater vehicle, and use the grid method to grid the three-dimensional sea environment. The gridding scale is based on the diving speed and path accuracy requirements of the underwater vehicle itself, and the sea environment is divided into m×n×l grid units of the same size.
3. The method for analyzing ocean three-dimensional routes based on meteorological and hydrological data according to claim 1, characterized in that: Step 2: Place the inaccessible area elements in the rasterized sea area, construct the obstacle matrix of the map environment model, and represent the free passage units and obstacle units, where: Elements of impassable areas include submarine obstacles, shipwrecks, reefs, sea basins, sea ridges, trenches, derricks, offshore platforms and oil and gas fields.
4. The method for analyzing ocean three-dimensional routes based on meteorological and hydrological data according to claim 1, characterized in that: Step 2: Place the inaccessible area elements in the rasterized sea area, construct the obstacle matrix of the map environment model, and characterize the free passage units and obstacle units. The specific method is as follows: The binary barrier information of any grid cell in the environment is defined as follows: Among them, (x, y, z) represents the position coordinates of grid p; The obstacle matrix of the map environment model is expressed as: map[m][n][l]={p(i,j,k),0≤i≤m,0≤j≤n,0≤k≤l} Among them, m, n, and l represent the number of grids divided by the x-axis, y-axis, and z-axis respectively, i represents the x-axis coordinate value of point p, j represents the y-axis coordinate value of point p, and k represents the z-axis coordinate value of point p.
5. The method for analyzing ocean three-dimensional routes based on meteorological and hydrological data according to claim 1, characterized in that: Step 3: construct functions of the marine environmental factors that affect the underwater vehicle route from the two aspects of thermocline and density cline. The specific method is as follows: Step 3.1, establish the thermocline environment function: Among them, K p represents the thermocline strength of grid cell p, Z k and T k Represents the depth and water temperature of the point p with a z-axis coordinate value of k in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis. Step 3.2, establish the density jump layer environment function: Among them, ρ p represents the density jump strength of grid cell p, Z k and ρ k Represents the depth and density of the z-axis coordinate value k at point p in the vertical gradient direction, where 0≤k≤l-1, and l is the number of grids divided on the z-axis.
6. The method for analyzing ocean three-dimensional routes based on meteorological and hydrological data according to claim 5 is characterized in that: Step 4: Based on the ocean environment, the dissipation function g(p) and heuristic function h(p) of the traditional A* algorithm are improved, and the ocean environment information such as the temperature jump layer and density jump layer of the grid sea area are combined to form the final evaluation cost f(p). The specific method is: Step 4.1, establish the energy consumption model of underwater vehicle: W=W X +W Y +W Z =∑ i＝1 (τ Xi x i +τ Yi y i +τ Zi z i ) ∑ i＝1 (t Xi +t Yi +t Zi )=τ Where W represents the total energy of the underwater vehicle, τ represents the number of grids where the underwater vehicle consumes all the energy to dive, and W X ,W Y ,W Z They represent the energy consumed by the underwater vehicle in the X, Y and Z directions respectively, i ,y i ,z i Respectively represent the unit length of the grid that the underwater vehicle passes through in the X, Y and Z directions, τ Xi ,τ yi ,τ zi They represent the number of grids in which the underwater vehicle consumes all its energy to dive in the X, Y and Z directions respectively; Step 4.2, define the dissipation function g(p): The temperature jump layer and density jump layer environment function are introduced, and the energy consumption of the underwater vehicle moving from the current grid to the next adjacent grid is defined as the dissipation function g(p), which is expressed as: In the formula, K p represents the thermocline environment function, ρ p represents the density jump layer environment function. Step 4.3, define the heuristic function h(p): The average speed of the grid passed by the connection between the intermediate node and the end point, that is, the end point fitness, is defined as the heuristic function h(p), which is expressed as: Among them, p is the current node number, ω is the weight coefficient, is the average speed of the grids passed by the line connecting the current node and the end point, v max is the speed of the grid with the maximum speed among the grids that the line passes through, and m is the number of grids that the line passes through; Step 4.3, construct the final evaluation cost function The final evaluation cost function f(p) is expressed as:
7. A three-dimensional ocean route analysis system based on meteorological and hydrological data, characterized in that: The method for analyzing ocean stereoscopic routes based on meteorological and hydrological data described in any one of claims 1 to 6 is implemented to realize ocean stereoscopic route analysis based on meteorological and hydrological data, which is divided into five modules and executes steps 1 to 5 respectively.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the ocean stereoscopic route analysis method based on meteorological and hydrological data according to any one of claims 1 to 6 is implemented to realize ocean stereoscopic route analysis based on meteorological and hydrological data.
9. A computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for analyzing ocean stereoscopic routes based on meteorological and hydrological data according to any one of claims 1 to 6 is implemented to realize the ocean stereoscopic route analysis based on meteorological and hydrological data.